Overview

Brought to you by YData

Dataset statistics

Number of variables16
Number of observations52413
Missing cells71075
Missing cells (%)8.5%
Duplicate rows1127
Duplicate rows (%)2.2%
Total size in memory8.8 MiB
Average record size in memory176.3 B

Variable types

Numeric15
Categorical1

Alerts

Dataset has 1127 (2.2%) duplicate rowsDuplicates
14614_FERM0101.PUMP_1_PV is highly imbalanced (99.9%)Imbalance
14614_FERM0101.Agitation_PV has 4443 (8.5%) missing valuesMissing
14614_FERM0101.Air_Sparge_PV has 4443 (8.5%) missing valuesMissing
14614_FERM0101.Biocontainer_Pressure_PV has 4442 (8.5%) missing valuesMissing
14614_FERM0101.DO_1_PV has 4443 (8.5%) missing valuesMissing
14614_FERM0101.DO_2_PV has 4442 (8.5%) missing valuesMissing
14614_FERM0101.Gas_Overlay_PV has 4443 (8.5%) missing valuesMissing
14614_FERM0101.Load_Cell_Net_PV has 4441 (8.5%) missing valuesMissing
14614_FERM0101.pH_1_PV has 4441 (8.5%) missing valuesMissing
14614_FERM0101.pH_2_PV has 4441 (8.5%) missing valuesMissing
14614_FERM0101.PUMP_1_PV has 4443 (8.5%) missing valuesMissing
14614_FERM0101.PUMP_1_TOTAL has 4441 (8.5%) missing valuesMissing
14614_FERM0101.PUMP_2_PV has 4443 (8.5%) missing valuesMissing
14614_FERM0101.PUMP_2_TOTAL has 4441 (8.5%) missing valuesMissing
14614_FERM0101.Single_Use_DO_PV has 4443 (8.5%) missing valuesMissing
14614_FERM0101.Single_Use_pH_PV has 4443 (8.5%) missing valuesMissing
14614_FERM0101.Temperatura_PV has 4442 (8.5%) missing valuesMissing
14614_FERM0101.Agitation_PV has 24167 (46.1%) zerosZeros
14614_FERM0101.Air_Sparge_PV has 44780 (85.4%) zerosZeros
14614_FERM0101.DO_1_PV has 36724 (70.1%) zerosZeros
14614_FERM0101.DO_2_PV has 798 (1.5%) zerosZeros
14614_FERM0101.Gas_Overlay_PV has 14898 (28.4%) zerosZeros
14614_FERM0101.Load_Cell_Net_PV has 3043 (5.8%) zerosZeros
14614_FERM0101.PUMP_1_TOTAL has 4358 (8.3%) zerosZeros
14614_FERM0101.PUMP_2_PV has 42169 (80.5%) zerosZeros
14614_FERM0101.PUMP_2_TOTAL has 13659 (26.1%) zerosZeros

Reproduction

Analysis started2024-09-29 18:18:59.737831
Analysis finished2024-09-29 18:19:18.221259
Duration18.48 seconds
Software versionydata-profiling v0.0.dev0
Download configurationconfig.json

Variables

14614_FERM0101.Agitation_PV
Real number (ℝ)

MISSING  ZEROS 

Distinct1020
Distinct (%)2.1%
Missing4443
Missing (%)8.5%
Infinite0
Infinite (%)0.0%
Mean27.900242
Minimum0
Maximum80
Zeros24167
Zeros (%)46.1%
Negative0
Negative (%)0.0%
Memory size2.8 MiB
2024-09-29T20:19:18.267320image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q380
95-th percentile80
Maximum80
Range80
Interquartile range (IQR)80

Descriptive statistics

Standard deviation34.386795
Coefficient of variation (CV)1.2324909
Kurtosis-1.2813206
Mean27.900242
Median Absolute Deviation (MAD)0
Skewness0.72235669
Sum1338374.6
Variance1182.4516
MonotonicityNot monotonic
2024-09-29T20:19:18.344416image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 24167
46.1%
80 13464
25.7%
20 5567
 
10.6%
36 916
 
1.7%
44 298
 
0.6%
21.37142792 176
 
0.3%
21.29714355 164
 
0.3%
21.31999969 133
 
0.3%
21.42857208 129
 
0.2%
21.34857178 122
 
0.2%
Other values (1010) 2834
 
5.4%
(Missing) 4443
 
8.5%
ValueCountFrequency (%)
0 24167
46.1%
20 5567
 
10.6%
20.02835218 1
 
< 0.1%
20.0422649 1
 
< 0.1%
20.04531503 1
 
< 0.1%
20.16439566 1
 
< 0.1%
20.20978204 1
 
< 0.1%
20.25040545 1
 
< 0.1%
20.25352509 1
 
< 0.1%
20.26692249 1
 
< 0.1%
ValueCountFrequency (%)
80 13464
25.7%
79.99995117 1
 
< 0.1%
79.99990776 1
 
< 0.1%
79.99987793 2
 
< 0.1%
79.99980469 1
 
< 0.1%
79.99973426 1
 
< 0.1%
79.99966104 1
 
< 0.1%
79.99959106 1
 
< 0.1%
79.99951782 1
 
< 0.1%
79.99944458 1
 
< 0.1%

14614_FERM0101.Air_Sparge_PV
Real number (ℝ)

MISSING  ZEROS 

Distinct3191
Distinct (%)6.7%
Missing4443
Missing (%)8.5%
Infinite0
Infinite (%)0.0%
Mean2.6275696
Minimum0
Maximum160.19078
Zeros44780
Zeros (%)85.4%
Negative0
Negative (%)0.0%
Memory size2.8 MiB
2024-09-29T20:19:18.417017image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile15.675899
Maximum160.19078
Range160.19078
Interquartile range (IQR)0

Descriptive statistics

Standard deviation11.698932
Coefficient of variation (CV)4.4523776
Kurtosis22.984309
Mean2.6275696
Median Absolute Deviation (MAD)0
Skewness4.7554121
Sum126044.51
Variance136.86501
MonotonicityNot monotonic
2024-09-29T20:19:18.491135image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 44780
85.4%
64.03632506 1
 
< 0.1%
3.895536039 1
 
< 0.1%
48.41283264 1
 
< 0.1%
43.18330688 1
 
< 0.1%
20.9385376 1
 
< 0.1%
35.79204102 1
 
< 0.1%
64.2014824 1
 
< 0.1%
57.31350704 1
 
< 0.1%
2.067433674 1
 
< 0.1%
Other values (3181) 3181
 
6.1%
(Missing) 4443
 
8.5%
ValueCountFrequency (%)
0 44780
85.4%
0.02109119767 1
 
< 0.1%
0.05705180119 1
 
< 0.1%
0.07309671369 1
 
< 0.1%
0.3587397935 1
 
< 0.1%
0.5389832687 1
 
< 0.1%
0.5485125995 1
 
< 0.1%
0.5515619084 1
 
< 0.1%
0.5875961582 1
 
< 0.1%
0.6050339625 1
 
< 0.1%
ValueCountFrequency (%)
160.1907792 1
< 0.1%
160.0663767 1
< 0.1%
160.0267274 1
< 0.1%
160.0047298 1
< 0.1%
160.0003273 1
< 0.1%
120.0437617 1
< 0.1%
64.81674805 1
< 0.1%
64.78876797 1
< 0.1%
64.78068848 1
< 0.1%
64.76985056 1
< 0.1%

14614_FERM0101.Biocontainer_Pressure_PV
Real number (ℝ)

MISSING 

Distinct24166
Distinct (%)50.4%
Missing4442
Missing (%)8.5%
Infinite0
Infinite (%)0.0%
Mean128.60199
Minimum-14.839222
Maximum480
Zeros0
Zeros (%)0.0%
Negative24540
Negative (%)46.8%
Memory size2.8 MiB
2024-09-29T20:19:18.565260image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum-14.839222
5-th percentile-2.1412048
Q1-0.80440063
median-0.095483398
Q3480
95-th percentile480
Maximum480
Range494.83922
Interquartile range (IQR)480.8044

Descriptive statistics

Standard deviation212.84355
Coefficient of variation (CV)1.6550563
Kurtosis-0.90732871
Mean128.60199
Median Absolute Deviation (MAD)1.4178284
Skewness1.0451989
Sum6169166.3
Variance45302.375
MonotonicityNot monotonic
2024-09-29T20:19:18.641368image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
480 12875
 
24.6%
-0.561340332 389
 
0.7%
-0.5410888672 348
 
0.7%
-0.6018493652 292
 
0.6%
-0.7841430664 253
 
0.5%
-0.5208312988 222
 
0.4%
-0.3182861328 216
 
0.4%
-0.358795166 212
 
0.4%
-0.8044006348 203
 
0.4%
-0.7638916016 196
 
0.4%
Other values (24156) 32765
62.5%
(Missing) 4442
 
8.5%
ValueCountFrequency (%)
-14.83922177 1
< 0.1%
-7.974536133 1
< 0.1%
-7.95833374 1
< 0.1%
-7.9340271 1
< 0.1%
-7.925794144 1
< 0.1%
-7.925742318 1
< 0.1%
-7.925702057 1
< 0.1%
-7.922063884 1
< 0.1%
-7.917659624 1
< 0.1%
-7.913775635 2
< 0.1%
ValueCountFrequency (%)
480 12875
24.6%
100.78631 1
 
< 0.1%
8.823789252 1
 
< 0.1%
8.776043701 1
 
< 0.1%
8.565524652 1
 
< 0.1%
8.528460663 1
 
< 0.1%
8.382399687 1
 
< 0.1%
8.350695801 1
 
< 0.1%
8.346190495 1
 
< 0.1%
8.326273786 1
 
< 0.1%

14614_FERM0101.DO_1_PV
Real number (ℝ)

MISSING  ZEROS 

Distinct7080
Distinct (%)14.8%
Missing4443
Missing (%)8.5%
Infinite0
Infinite (%)0.0%
Mean6.1954184
Minimum0
Maximum123.74879
Zeros36724
Zeros (%)70.1%
Negative0
Negative (%)0.0%
Memory size2.8 MiB
2024-09-29T20:19:18.713989image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile27.447801
Maximum123.74879
Range123.74879
Interquartile range (IQR)0

Descriptive statistics

Standard deviation14.4918
Coefficient of variation (CV)2.3391156
Kurtosis11.482805
Mean6.1954184
Median Absolute Deviation (MAD)0
Skewness3.1890449
Sum297194.22
Variance210.01226
MonotonicityNot monotonic
2024-09-29T20:19:18.789638image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 36724
70.1%
60.9762207 62
 
0.1%
60.81130981 48
 
0.1%
61.62409058 42
 
0.1%
60.64639282 35
 
0.1%
61.78311157 33
 
0.1%
61.30015259 32
 
0.1%
61.46506348 31
 
0.1%
24 30
 
0.1%
23.86440582 28
 
0.1%
Other values (7070) 10905
 
20.8%
(Missing) 4443
 
8.5%
ValueCountFrequency (%)
0 36724
70.1%
1.968612671 2
 
< 0.1%
2.044151688 1
 
< 0.1%
2.104205894 1
 
< 0.1%
2.474275711 1
 
< 0.1%
2.714159775 1
 
< 0.1%
2.745025444 1
 
< 0.1%
2.762215233 1
 
< 0.1%
2.797237778 1
 
< 0.1%
2.916890144 1
 
< 0.1%
ValueCountFrequency (%)
123.7487915 1
< 0.1%
123.419038 1
< 0.1%
122.9360229 1
< 0.1%
121.6285034 2
< 0.1%
120.9864513 1
< 0.1%
120.3327637 1
< 0.1%
119.6790039 1
< 0.1%
119.3550781 2
< 0.1%
118.3773804 1
< 0.1%
117.4055786 1
< 0.1%

14614_FERM0101.DO_2_PV
Real number (ℝ)

MISSING  ZEROS 

Distinct194
Distinct (%)0.4%
Missing4442
Missing (%)8.5%
Infinite0
Infinite (%)0.0%
Mean-0.0054270918
Minimum-0.0055297852
Maximum0
Zeros798
Zeros (%)1.5%
Negative47173
Negative (%)90.0%
Memory size2.8 MiB
2024-09-29T20:19:18.861218image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum-0.0055297852
5-th percentile-0.0055297852
Q1-0.0055297852
median-0.0055297852
Q3-0.0055297852
95-th percentile-0.0055297852
Maximum0
Range0.0055297852
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.00073309919
Coefficient of variation (CV)-0.13508141
Kurtosis49.25955
Mean-0.0054270918
Median Absolute Deviation (MAD)0
Skewness7.1291559
Sum-260.34302
Variance5.3743443 × 10-7
MonotonicityNot monotonic
2024-09-29T20:19:18.930037image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-0.005529785156 46981
89.6%
0 798
 
1.5%
-0.005498022616 1
 
< 0.1%
-4.127386787 × 10-51
 
< 0.1%
-0.003712262376 1
 
< 0.1%
-0.001868777995 1
 
< 0.1%
-0.003717401092 1
 
< 0.1%
-0.003732081068 1
 
< 0.1%
-0.001754717299 1
 
< 0.1%
-0.003630011928 1
 
< 0.1%
Other values (184) 184
 
0.4%
(Missing) 4442
 
8.5%
ValueCountFrequency (%)
-0.005529785156 46981
89.6%
-0.005525782548 1
 
< 0.1%
-0.005519367462 1
 
< 0.1%
-0.005519161521 1
 
< 0.1%
-0.005514969802 1
 
< 0.1%
-0.005509946854 1
 
< 0.1%
-0.005508064171 1
 
< 0.1%
-0.005506218395 1
 
< 0.1%
-0.005506047471 1
 
< 0.1%
-0.00550602079 1
 
< 0.1%
ValueCountFrequency (%)
0 798
1.5%
-1.076936429 × 10-51
 
< 0.1%
-1.59191062 × 10-51
 
< 0.1%
-2.320291786 × 10-51
 
< 0.1%
-2.336014851 × 10-51
 
< 0.1%
-2.37620094 × 10-51
 
< 0.1%
-2.411482509 × 10-51
 
< 0.1%
-2.513373136 × 10-51
 
< 0.1%
-2.578558769 × 10-51
 
< 0.1%
-4.127386787 × 10-51
 
< 0.1%

14614_FERM0101.Gas_Overlay_PV
Real number (ℝ)

MISSING  ZEROS 

Distinct33072
Distinct (%)68.9%
Missing4443
Missing (%)8.5%
Infinite0
Infinite (%)0.0%
Mean3.179065
Minimum0
Maximum16.00189
Zeros14898
Zeros (%)28.4%
Negative0
Negative (%)0.0%
Memory size2.8 MiB
2024-09-29T20:19:19.000669image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3.9999004
Q34.0001589
95-th percentile8.0000371
Maximum16.00189
Range16.00189
Interquartile range (IQR)4.0001589

Descriptive statistics

Standard deviation2.4580587
Coefficient of variation (CV)0.77320179
Kurtosis-0.16601591
Mean3.179065
Median Absolute Deviation (MAD)0.00040115006
Skewness0.21676054
Sum152499.75
Variance6.0420527
MonotonicityNot monotonic
2024-09-29T20:19:19.074836image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 14898
28.4%
4.00022876 2
 
< 0.1%
3.999897931 1
 
< 0.1%
4.000495985 1
 
< 0.1%
4.000203697 1
 
< 0.1%
4.000098686 1
 
< 0.1%
3.999763695 1
 
< 0.1%
4.000103467 1
 
< 0.1%
4.000076582 1
 
< 0.1%
4.000314152 1
 
< 0.1%
Other values (33062) 33062
63.1%
(Missing) 4443
 
8.5%
ValueCountFrequency (%)
0 14898
28.4%
3.914580031 1
 
< 0.1%
3.940651901 1
 
< 0.1%
3.946993617 1
 
< 0.1%
3.94966657 1
 
< 0.1%
3.971746528 1
 
< 0.1%
3.974199433 1
 
< 0.1%
3.974584943 1
 
< 0.1%
3.975356097 1
 
< 0.1%
3.981934242 1
 
< 0.1%
ValueCountFrequency (%)
16.0018895 1
< 0.1%
16.00186141 1
< 0.1%
16.00156172 1
< 0.1%
16.00143951 1
< 0.1%
16.00127856 1
< 0.1%
16.00120293 1
< 0.1%
16.00112952 1
< 0.1%
16.00109532 1
< 0.1%
16.0009344 1
< 0.1%
16.00064899 1
< 0.1%

14614_FERM0101.Load_Cell_Net_PV
Real number (ℝ)

MISSING  ZEROS 

Distinct1994
Distinct (%)4.2%
Missing4441
Missing (%)8.5%
Infinite0
Infinite (%)0.0%
Mean723.1992
Minimum-22.8
Maximum1720.4
Zeros3043
Zeros (%)5.8%
Negative12693
Negative (%)24.2%
Memory size2.8 MiB
2024-09-29T20:19:19.147966image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum-22.8
5-th percentile-18
Q1-1.2
median288
Q31586
95-th percentile1663.2
Maximum1720.4
Range1743.2
Interquartile range (IQR)1587.2

Descriptive statistics

Standard deviation780.33277
Coefficient of variation (CV)1.0790012
Kurtosis-1.8957406
Mean723.1992
Median Absolute Deviation (MAD)306
Skewness0.23373129
Sum34693312
Variance608919.23
MonotonicityNot monotonic
2024-09-29T20:19:19.219638image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 3043
 
5.8%
-17.6 2974
 
5.7%
0.4 2376
 
4.5%
-17.2 1467
 
2.8%
1.6 1359
 
2.6%
0.8 1279
 
2.4%
-16 1252
 
2.4%
-18 1067
 
2.0%
-18.4 860
 
1.6%
287.6 676
 
1.3%
Other values (1984) 31619
60.3%
(Missing) 4441
 
8.5%
ValueCountFrequency (%)
-22.8 2
 
< 0.1%
-22.4 4
 
< 0.1%
-22 7
 
< 0.1%
-21.6 15
 
< 0.1%
-21.43221008 1
 
< 0.1%
-21.28679171 1
 
< 0.1%
-21.2 88
 
0.2%
-20.88435876 1
 
< 0.1%
-20.8 26
 
< 0.1%
-20.4 546
1.0%
ValueCountFrequency (%)
1720.4 1
 
< 0.1%
1718 6
 
< 0.1%
1717.6 14
 
< 0.1%
1717.2 15
 
< 0.1%
1716.8 27
0.1%
1716.4 36
0.1%
1716.211284 1
 
< 0.1%
1716 64
0.1%
1715.788196 1
 
< 0.1%
1715.785559 1
 
< 0.1%

14614_FERM0101.pH_1_PV
Real number (ℝ)

MISSING 

Distinct6905
Distinct (%)14.4%
Missing4441
Missing (%)8.5%
Infinite0
Infinite (%)0.0%
Mean3.0782091
Minimum-0.1569252
Maximum9.2455765
Zeros1
Zeros (%)< 0.1%
Negative3609
Negative (%)6.9%
Memory size2.8 MiB
2024-09-29T20:19:19.293726image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum-0.1569252
5-th percentile-0.1569252
Q11.5162798
median1.6305742
Q35.8035332
95-th percentile5.9278736
Maximum9.2455765
Range9.4025017
Interquartile range (IQR)4.2872534

Descriptive statistics

Standard deviation2.1877935
Coefficient of variation (CV)0.71073585
Kurtosis-1.5621181
Mean3.0782091
Median Absolute Deviation (MAD)0.30771618
Skewness0.33298182
Sum147667.85
Variance4.7864406
MonotonicityNot monotonic
2024-09-29T20:19:19.363316image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-0.1569252014 3568
 
6.8%
1.630574226 3078
 
5.9%
1.574962616 2542
 
4.8%
1.608564568 1750
 
3.3%
1.516279793 1622
 
3.1%
1.415245438 1354
 
2.6%
1.467676544 743
 
1.4%
1.507746124 671
 
1.3%
2.077318001 663
 
1.3%
1.594210625 655
 
1.2%
Other values (6895) 31326
59.8%
(Missing) 4441
 
8.5%
ValueCountFrequency (%)
-0.1569252014 3568
6.8%
-0.1565112327 1
 
< 0.1%
-0.1559034253 1
 
< 0.1%
-0.1553880936 1
 
< 0.1%
-0.153054663 1
 
< 0.1%
-0.08170127869 30
 
0.1%
-0.00399076574 1
 
< 0.1%
-0.003318315235 1
 
< 0.1%
-0.00178429881 1
 
< 0.1%
-0.001016301199 1
 
< 0.1%
ValueCountFrequency (%)
9.245576477 3
< 0.1%
8.161817269 1
 
< 0.1%
7.172860718 2
< 0.1%
7.164474487 2
< 0.1%
7.164173889 1
 
< 0.1%
7.157164982 1
 
< 0.1%
7.156086731 1
 
< 0.1%
7.1477005 1
 
< 0.1%
7.133515082 1
 
< 0.1%
7.131227112 1
 
< 0.1%

14614_FERM0101.pH_2_PV
Real number (ℝ)

MISSING 

Distinct485
Distinct (%)1.0%
Missing4441
Missing (%)8.5%
Infinite0
Infinite (%)0.0%
Mean0.0006559883
Minimum-0.2552742
Maximum6.2715607
Zeros51
Zeros (%)0.1%
Negative43923
Negative (%)83.8%
Memory size2.8 MiB
2024-09-29T20:19:19.430444image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum-0.2552742
5-th percentile-0.2552742
Q1-0.2552742
median-0.2552742
Q3-0.2552742
95-th percentile1.4764116
Maximum6.2715607
Range6.5268349
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.0185674
Coefficient of variation (CV)1552.7219
Kurtosis24.152981
Mean0.0006559883
Median Absolute Deviation (MAD)0
Skewness4.862188
Sum31.469071
Variance1.0374796
MonotonicityNot monotonic
2024-09-29T20:19:19.501068image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-0.2552742004 42468
81.0%
-0.1729745865 1359
 
2.6%
1.476411629 1228
 
2.3%
1.383937836 473
 
0.9%
1.443000412 470
 
0.9%
1.35053196 292
 
0.6%
1.493390465 137
 
0.3%
1.460891533 103
 
0.2%
5.879973984 101
 
0.2%
5.880183792 80
 
0.2%
Other values (475) 1261
 
2.4%
(Missing) 4441
 
8.5%
ValueCountFrequency (%)
-0.2552742004 42468
81.0%
-0.2540766011 1
 
< 0.1%
-0.2531920999 1
 
< 0.1%
-0.2491811525 1
 
< 0.1%
-0.2203835778 1
 
< 0.1%
-0.2199618879 1
 
< 0.1%
-0.2176203286 1
 
< 0.1%
-0.2147413668 1
 
< 0.1%
-0.204073875 1
 
< 0.1%
-0.2038362761 1
 
< 0.1%
ValueCountFrequency (%)
6.271560669 1
 
< 0.1%
6.270639374 1
 
< 0.1%
6.223144024 1
 
< 0.1%
6.158400369 1
 
< 0.1%
6.153872488 1
 
< 0.1%
5.960367203 1
 
< 0.1%
5.952719879 1
 
< 0.1%
5.952261734 20
< 0.1%
5.952257677 1
 
< 0.1%
5.951976733 1
 
< 0.1%

14614_FERM0101.PUMP_1_PV
Categorical

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing4443
Missing (%)8.5%
Memory size2.8 MiB
0.0
47966 
48.0
 
4

Length

Max length4
Median length3
Mean length3.0000834
Min length3

Characters and Unicode

Total characters143914
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 47966
91.5%
48.0 4
 
< 0.1%
(Missing) 4443
 
8.5%

Length

2024-09-29T20:19:19.568838image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-09-29T20:19:19.617943image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
ValueCountFrequency (%)
0.0 47966
> 99.9%
48.0 4
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 95936
66.7%
. 47970
33.3%
4 4
 
< 0.1%
8 4
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 143914
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 95936
66.7%
. 47970
33.3%
4 4
 
< 0.1%
8 4
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 143914
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 95936
66.7%
. 47970
33.3%
4 4
 
< 0.1%
8 4
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 143914
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 95936
66.7%
. 47970
33.3%
4 4
 
< 0.1%
8 4
 
< 0.1%

14614_FERM0101.PUMP_1_TOTAL
Real number (ℝ)

MISSING  ZEROS 

Distinct154
Distinct (%)0.3%
Missing4441
Missing (%)8.5%
Infinite0
Infinite (%)0.0%
Mean45.618193
Minimum0
Maximum1386.3174
Zeros4358
Zeros (%)8.3%
Negative0
Negative (%)0.0%
Memory size2.8 MiB
2024-09-29T20:19:19.670756image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q114.88
median32.239999
Q359.519989
95-th percentile124.00001
Maximum1386.3174
Range1386.3174
Interquartile range (IQR)44.639989

Descriptive statistics

Standard deviation69.663801
Coefficient of variation (CV)1.5271056
Kurtosis204.0997
Mean45.618193
Median Absolute Deviation (MAD)19.839999
Skewness11.662042
Sum2188396
Variance4853.0451
MonotonicityNot monotonic
2024-09-29T20:19:19.741135image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
59.51998901 7352
 
14.0%
0 4358
 
8.3%
17.36000061 3665
 
7.0%
14.88000031 3156
 
6.0%
32.23999939 2287
 
4.4%
22.32000122 1890
 
3.6%
52.07999268 1881
 
3.6%
12.4 1799
 
3.4%
29.76000061 1603
 
3.1%
42.15999451 1416
 
2.7%
Other values (144) 18565
35.4%
(Missing) 4441
 
8.5%
ValueCountFrequency (%)
0 4358
8.3%
0.01114275186 1
 
< 0.1%
0.1116374531 1
 
< 0.1%
0.1157202362 1
 
< 0.1%
0.3298607358 1
 
< 0.1%
0.3997990558 1
 
< 0.1%
0.5586227134 1
 
< 0.1%
0.7450066611 1
 
< 0.1%
0.7606427221 1
 
< 0.1%
0.8721910705 1
 
< 0.1%
ValueCountFrequency (%)
1386.317383 47
 
0.1%
1306.958008 31
 
0.1%
524.5208984 1
 
< 0.1%
369.5204834 205
 
0.4%
250.480249 587
1.1%
248.0002441 1
 
< 0.1%
244.7290937 1
 
< 0.1%
193.4401489 125
 
0.2%
188.4801392 1
 
< 0.1%
183.5201294 9
 
< 0.1%

14614_FERM0101.PUMP_2_PV
Real number (ℝ)

MISSING  ZEROS 

Distinct5352
Distinct (%)11.2%
Missing4443
Missing (%)8.5%
Infinite0
Infinite (%)0.0%
Mean0.43132216
Minimum0
Maximum80
Zeros42169
Zeros (%)80.5%
Negative0
Negative (%)0.0%
Memory size2.8 MiB
2024-09-29T20:19:19.813678image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile4.058254
Maximum80
Range80
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.5674804
Coefficient of variation (CV)3.6341291
Kurtosis150.74845
Mean0.43132216
Median Absolute Deviation (MAD)0
Skewness6.2736182
Sum20690.524
Variance2.4569948
MonotonicityNot monotonic
2024-09-29T20:19:19.888487image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 42169
80.5%
8 435
 
0.8%
0.4860099792 3
 
< 0.1%
4.270703125 2
 
< 0.1%
5.291605377 2
 
< 0.1%
0.3483711243 2
 
< 0.1%
0.3324436188 2
 
< 0.1%
0.3272274017 2
 
< 0.1%
6.746477509 2
 
< 0.1%
0.2966644287 2
 
< 0.1%
Other values (5342) 5349
 
10.2%
(Missing) 4443
 
8.5%
ValueCountFrequency (%)
0 42169
80.5%
3.051757858 × 10-71
 
< 0.1%
8.585711509 × 10-71
 
< 0.1%
3.277489783 × 10-61
 
< 0.1%
4.588888731 × 10-61
 
< 0.1%
1.266804469 × 10-51
 
< 0.1%
2.228564413 × 10-51
 
< 0.1%
2.31698436 × 10-51
 
< 0.1%
2.376482648 × 10-51
 
< 0.1%
2.86196768 × 10-51
 
< 0.1%
ValueCountFrequency (%)
80 1
 
< 0.1%
9.729266551 1
 
< 0.1%
8 435
0.8%
7.999993618 1
 
< 0.1%
7.999988779 1
 
< 0.1%
7.999957179 1
 
< 0.1%
7.999916338 1
 
< 0.1%
7.999892303 1
 
< 0.1%
7.999875095 1
 
< 0.1%
7.999862706 1
 
< 0.1%

14614_FERM0101.PUMP_2_TOTAL
Real number (ℝ)

MISSING  ZEROS 

Distinct7456
Distinct (%)15.5%
Missing4441
Missing (%)8.5%
Infinite0
Infinite (%)0.0%
Mean3540.2579
Minimum0
Maximum11414.281
Zeros13659
Zeros (%)26.1%
Negative0
Negative (%)0.0%
Memory size2.8 MiB
2024-09-29T20:19:19.962622image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3124.1946
Q36825.2219
95-th percentile8553.7383
Maximum11414.281
Range11414.281
Interquartile range (IQR)6825.2219

Descriptive statistics

Standard deviation3448.0113
Coefficient of variation (CV)0.97394354
Kurtosis-1.4367524
Mean3540.2579
Median Absolute Deviation (MAD)3124.1946
Skewness0.3362611
Sum1.6983325 × 108
Variance11888782
MonotonicityNot monotonic
2024-09-29T20:19:20.034244image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 13659
26.1%
8099.764844 3942
 
7.5%
4386.676172 3250
 
6.2%
1216.803125 1804
 
3.4%
6269.859375 1426
 
2.7%
9921.025781 1335
 
2.5%
3.324572372 1251
 
2.4%
7072.120313 959
 
1.8%
3485.444531 831
 
1.6%
5345.825781 766
 
1.5%
Other values (7446) 18749
35.8%
(Missing) 4441
 
8.5%
ValueCountFrequency (%)
0 13659
26.1%
1.064488316 12
 
< 0.1%
1.080545666 1
 
< 0.1%
2.257954248 1
 
< 0.1%
3.300000381 5
 
< 0.1%
3.324572372 1251
 
2.4%
6.773368073 2
 
< 0.1%
9.679997253 1
 
< 0.1%
10.09029083 1
 
< 0.1%
11.36431046 1
 
< 0.1%
ValueCountFrequency (%)
11414.28125 13
< 0.1%
11376.01484 2
 
< 0.1%
11326.74609 1
 
< 0.1%
11277.5375 1
 
< 0.1%
11221.17578 1
 
< 0.1%
11148.88359 1
 
< 0.1%
11085.65937 1
 
< 0.1%
11027.91484 1
 
< 0.1%
10970.77109 1
 
< 0.1%
10902.17008 1
 
< 0.1%

14614_FERM0101.Single_Use_DO_PV
Real number (ℝ)

MISSING 

Distinct9606
Distinct (%)20.0%
Missing4443
Missing (%)8.5%
Infinite0
Infinite (%)0.0%
Mean611.91945
Minimum0
Maximum870.78691
Zeros4
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size2.8 MiB
2024-09-29T20:19:20.106862image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile15.716135
Q1698.49995
median738.54502
Q3799.99199
95-th percentile799.99199
Maximum870.78691
Range870.78691
Interquartile range (IQR)101.49204

Descriptive statistics

Standard deviation300.29992
Coefficient of variation (CV)0.49075073
Kurtosis0.055427444
Mean611.91945
Median Absolute Deviation (MAD)61.446973
Skewness-1.398561
Sum29353776
Variance90180.04
MonotonicityNot monotonic
2024-09-29T20:19:20.175550image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
799.9919922 20325
38.8%
710.0310547 3947
 
7.5%
731.789209 3179
 
6.1%
698.4999512 1706
 
3.3%
675.6118164 970
 
1.9%
738.5450195 743
 
1.4%
765.030127 682
 
1.3%
736.5730469 590
 
1.1%
706.5194336 587
 
1.1%
701.5627441 578
 
1.1%
Other values (9596) 14663
28.0%
(Missing) 4443
 
8.5%
ValueCountFrequency (%)
0 4
< 0.1%
1.16503292 1
 
< 0.1%
1.176200375 1
 
< 0.1%
1.176242875 1
 
< 0.1%
1.236736202 1
 
< 0.1%
1.258690071 1
 
< 0.1%
1.307135902 1
 
< 0.1%
1.312023488 1
 
< 0.1%
1.332586335 1
 
< 0.1%
1.363273239 1
 
< 0.1%
ValueCountFrequency (%)
870.7869141 33
 
0.1%
818.573584 555
 
1.1%
799.9919922 20325
38.8%
798.867236 1
 
< 0.1%
786.7421384 1
 
< 0.1%
785.9657187 1
 
< 0.1%
785.0472949 1
 
< 0.1%
781.853943 1
 
< 0.1%
779.1584575 1
 
< 0.1%
772.3226796 1
 
< 0.1%

14614_FERM0101.Single_Use_pH_PV
Real number (ℝ)

MISSING 

Distinct823
Distinct (%)1.7%
Missing4443
Missing (%)8.5%
Infinite0
Infinite (%)0.0%
Mean556.63596
Minimum-794.22397
Maximum800.16001
Zeros0
Zeros (%)0.0%
Negative1489
Negative (%)2.8%
Memory size2.8 MiB
2024-09-29T20:19:20.240221image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum-794.22397
5-th percentile5.7600002
Q15.9120117
median799.92798
Q3799.97598
95-th percentile800.05601
Maximum800.16001
Range1594.384
Interquartile range (IQR)794.06396

Descriptive statistics

Standard deviation376.54357
Coefficient of variation (CV)0.67646288
Kurtosis-0.53940081
Mean556.63596
Median Absolute Deviation (MAD)0.072021484
Skewness-1.0105634
Sum26701827
Variance141785.06
MonotonicityNot monotonic
2024-09-29T20:19:20.314246image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
799.9439941 6303
 
12.0%
800 5663
 
10.8%
799.8799805 2733
 
5.2%
799.9600098 2469
 
4.7%
799.8239746 2124
 
4.1%
799.9279785 1822
 
3.5%
800.0560059 1781
 
3.4%
800.0719727 1703
 
3.2%
799.9759766 1604
 
3.1%
799.9120117 1540
 
2.9%
Other values (813) 20228
38.6%
(Missing) 4443
 
8.5%
ValueCountFrequency (%)
-794.2239746 2
 
< 0.1%
-794.1839844 10
< 0.1%
-793.8719727 1
 
< 0.1%
-791.847998 1
 
< 0.1%
-788.352002 1
 
< 0.1%
-788.2880371 1
 
< 0.1%
-788.2800293 2
 
< 0.1%
-787.9759766 2
 
< 0.1%
-787.9679688 15
< 0.1%
-787.9600098 10
< 0.1%
ValueCountFrequency (%)
800.1600098 453
 
0.9%
800.0719727 1703
 
3.2%
800.0560059 1781
 
3.4%
800.0239746 456
 
0.9%
800.0160156 351
 
0.7%
800 5663
10.8%
799.9759766 1604
 
3.1%
799.9679688 1341
 
2.6%
799.9600098 2469
 
4.7%
799.9439941 6303
12.0%

14614_FERM0101.Temperatura_PV
Real number (ℝ)

MISSING 

Distinct23216
Distinct (%)48.4%
Missing4442
Missing (%)8.5%
Infinite0
Infinite (%)0.0%
Mean18.024732
Minimum3.047998
Maximum80.237275
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 MiB
2024-09-29T20:19:20.387676image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum3.047998
5-th percentile3.2
Q114.704004
median16.464001
Q325.085262
95-th percentile29.656006
Maximum80.237275
Range77.189277
Interquartile range (IQR)10.381258

Descriptive statistics

Standard deviation8.2069709
Coefficient of variation (CV)0.45531722
Kurtosis-0.66363415
Mean18.024732
Median Absolute Deviation (MAD)4.7839966
Skewness-0.084829379
Sum864664.42
Variance67.354372
MonotonicityNot monotonic
2024-09-29T20:19:20.465145image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
29.60799561 1158
 
2.2%
29.61600342 1015
 
1.9%
29.58399658 967
 
1.8%
3.2 965
 
1.8%
3.176000977 711
 
1.4%
3.208001709 681
 
1.3%
29.63199463 576
 
1.1%
29.56800537 495
 
0.9%
3.167999268 337
 
0.6%
3.232000732 327
 
0.6%
Other values (23206) 40739
77.7%
(Missing) 4442
 
8.5%
ValueCountFrequency (%)
3.047998047 3
 
< 0.1%
3.062177022 1
 
< 0.1%
3.07199707 10
< 0.1%
3.077288096 1
 
< 0.1%
3.077291028 1
 
< 0.1%
3.077302816 1
 
< 0.1%
3.078527917 1
 
< 0.1%
3.081546739 1
 
< 0.1%
3.088000488 8
< 0.1%
3.111999512 18
< 0.1%
ValueCountFrequency (%)
80.23727531 1
 
< 0.1%
30.34399414 1
 
< 0.1%
30.32805802 1
 
< 0.1%
30.32800293 1
 
< 0.1%
30.30400391 1
 
< 0.1%
30.29599609 6
< 0.1%
30.2907455 1
 
< 0.1%
30.28000488 5
< 0.1%
30.27652786 1
 
< 0.1%
30.26938352 1
 
< 0.1%

Interactions

2024-09-29T20:19:16.622783image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:19:00.425516image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:19:01.525497image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:19:02.593307image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:19:03.636986image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:19:04.668772image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:19:07.203147image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:19:08.268202image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:19:09.339195image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:19:10.333292image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:19:11.355876image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:19:12.418348image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:19:13.489687image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:19:14.522203image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:19:15.540598image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:19:16.695301image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:19:00.530626image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:19:01.599262image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
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2024-09-29T20:19:11.285832image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:19:12.343853image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:19:13.417015image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:19:14.450066image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:19:15.469494image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:19:16.546648image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Missing values

2024-09-29T20:19:17.708781image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
A simple visualization of nullity by column.
2024-09-29T20:19:17.859166image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2024-09-29T20:19:18.053516image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

14614_FERM0101.Agitation_PV14614_FERM0101.Air_Sparge_PV14614_FERM0101.Biocontainer_Pressure_PV14614_FERM0101.DO_1_PV14614_FERM0101.DO_2_PV14614_FERM0101.Gas_Overlay_PV14614_FERM0101.Load_Cell_Net_PV14614_FERM0101.pH_1_PV14614_FERM0101.pH_2_PV14614_FERM0101.PUMP_1_PV14614_FERM0101.PUMP_1_TOTAL14614_FERM0101.PUMP_2_PV14614_FERM0101.PUMP_2_TOTAL14614_FERM0101.Single_Use_DO_PV14614_FERM0101.Single_Use_pH_PV14614_FERM0101.Temperatura_PV
DateTime
2023-03-15 00:00:00.00080.00.00.5726600.0-0.005534.0000871576.8-0.1569255.8882880.014.880.0191.200293799.991992799.96796930.216161
2023-03-15 00:15:00.00080.00.00.4919420.0-0.005534.0000841576.8-0.1569255.8961040.014.880.0191.200293799.991992799.96796930.135999
2023-03-15 00:30:00.00080.00.00.5526880.0-0.005534.0001611576.8-0.1569255.8961040.014.880.0191.200293799.991992799.96796929.823988
2023-03-15 00:45:00.00080.00.00.6133180.0-0.005534.0000881576.8-0.1569255.8961040.014.880.0191.200293799.991992799.96796929.408039
2023-03-15 01:00:00.00080.00.00.5524210.0-0.005533.9998641577.2-0.1569255.9042100.014.880.0191.200293799.991992799.96796929.191720
2023-03-15 01:15:00.00080.00.00.6134280.0-0.005534.0001331577.2-0.1569255.9042100.014.880.0191.200293799.991992799.96796929.080505
2023-03-15 01:30:00.00080.00.00.5316800.0-0.005533.9998971577.2-0.1569255.9042100.014.880.0191.200293799.991992799.96796929.536295
2023-03-15 01:45:00.00080.00.00.5723800.0-0.005533.9996751577.2-0.1569255.8961040.014.880.0191.200293799.991992799.96796930.000000
2023-03-15 02:00:00.00080.00.00.5328380.0-0.005534.0000561576.8-0.1569255.9041240.014.880.0191.200293799.991992799.96796929.951748
2023-03-15 02:15:00.00080.00.00.4919010.0-0.005533.9999651576.8-0.1569255.9042100.014.880.0191.200293799.991992799.96796929.663946
14614_FERM0101.Agitation_PV14614_FERM0101.Air_Sparge_PV14614_FERM0101.Biocontainer_Pressure_PV14614_FERM0101.DO_1_PV14614_FERM0101.DO_2_PV14614_FERM0101.Gas_Overlay_PV14614_FERM0101.Load_Cell_Net_PV14614_FERM0101.pH_1_PV14614_FERM0101.pH_2_PV14614_FERM0101.PUMP_1_PV14614_FERM0101.PUMP_1_TOTAL14614_FERM0101.PUMP_2_PV14614_FERM0101.PUMP_2_TOTAL14614_FERM0101.Single_Use_DO_PV14614_FERM0101.Single_Use_pH_PV14614_FERM0101.Temperatura_PV
DateTime
2024-09-10 21:45:00.0000.00.0480.00.00.00.0-17.61.415245-0.1729750.059.5199890.08099.764844710.031055799.94399416.216003
2024-09-10 22:00:00.0000.00.0480.00.00.00.0-17.61.415245-0.1729750.059.5199890.08099.764844710.031055799.94399416.136935
2024-09-10 22:15:00.0000.00.0480.00.00.00.0-17.61.415245-0.1729750.059.5199890.08099.764844710.031055799.94399416.112000
2024-09-10 22:30:00.0000.00.0480.00.00.00.0-17.61.415245-0.1729750.059.5199890.08099.764844710.031055799.94399416.112000
2024-09-10 22:45:00.0000.00.0480.00.00.00.0-17.61.415245-0.1729750.059.5199890.08099.764844710.031055799.94399416.047079
2024-09-10 23:00:00.0000.00.0480.00.00.00.0-17.61.415245-0.1729750.059.5199890.08099.764844710.031055799.94399416.119995
2024-09-10 23:15:00.0000.00.0480.00.00.00.0-17.61.415245-0.1729750.059.5199890.08099.764844710.031055799.94399416.088000
2024-09-10 23:30:00.0000.00.0480.00.00.00.0-17.61.415245-0.1729750.059.5199890.08099.764844710.031055799.94399416.040002
2024-09-10 23:45:00.0000.00.0480.00.00.00.0-17.61.415245-0.1729750.059.5199890.08099.764844710.031055799.94399416.088000
2024-09-11 00:00:00.0000.00.0480.00.00.00.0-17.61.415245-0.1729750.059.5199890.08099.764844710.031055799.94399416.016003

Duplicate rows

Most frequently occurring

14614_FERM0101.Agitation_PV14614_FERM0101.Air_Sparge_PV14614_FERM0101.Biocontainer_Pressure_PV14614_FERM0101.DO_1_PV14614_FERM0101.DO_2_PV14614_FERM0101.Gas_Overlay_PV14614_FERM0101.Load_Cell_Net_PV14614_FERM0101.pH_1_PV14614_FERM0101.pH_2_PV14614_FERM0101.PUMP_1_PV14614_FERM0101.PUMP_1_TOTAL14614_FERM0101.PUMP_2_PV14614_FERM0101.PUMP_2_TOTAL14614_FERM0101.Single_Use_DO_PV14614_FERM0101.Single_Use_pH_PV14614_FERM0101.Temperatura_PV# duplicates
1126NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN4441
10710.00.0480.00.00.00.0-17.61.415245-0.1729750.059.5199890.08099.764844710.031055799.94399415.49599622
10700.00.0480.00.00.00.0-17.61.415245-0.1729750.059.5199890.08099.764844710.031055799.94399415.48000521
10730.00.0480.00.00.00.0-17.61.415245-0.1729750.059.5199890.08099.764844710.031055799.94399415.52800319
10770.00.0480.00.00.00.0-17.61.415245-0.1729750.059.5199890.08099.764844710.031055799.94399415.58399718
10690.00.0480.00.00.00.0-17.61.415245-0.1729750.059.5199890.08099.764844710.031055799.94399415.45600615
10720.00.0480.00.00.00.0-17.61.415245-0.1729750.059.5199890.08099.764844710.031055799.94399415.51999514
10790.00.0480.00.00.00.0-17.61.415245-0.1729750.059.5199890.08099.764844710.031055799.94399415.61600314
10740.00.0480.00.00.00.0-17.61.415245-0.1729750.059.5199890.08099.764844710.031055799.94399415.53599913
10760.00.0480.00.00.00.0-17.61.415245-0.1729750.059.5199890.08099.764844710.031055799.94399415.57600113